Qwen Image 2.1 vs Qwen Image 3.0

Qwen Image 2.1 and Qwen Image 3.0 side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.

Alibaba Cloud Image Generation

Qwen Image 2.1 vs Qwen Image 3.0 at a glance

Qwen Image 2.1 and Qwen Image 3.0 are both Alibaba Cloud models in the Image Generation category, available through the EmpirioLabs API.

Key differences

  • Qwen Image 2.1 is the newer release (Oct 2, 2026); Qwen Image 3.0 was released on Jul 21, 2026.
  • Capabilities listed only for Qwen Image 2.1: multi reference, transparent background.
  • Capabilities listed only for Qwen Image 3.0: multilingual text, dense layouts, photorealism.

Qwen Image 2.1 vs Qwen Image 3.0: specs

SpecQwen Image 2.1Qwen Image 3.0
Model IDqwen-image-2-1qwen-image-3-0
AuthorAlibaba CloudAlibaba Cloud
ReleasedOct 2, 2026Jul 21, 2026
Input
Text Image
Text Image
Output
Image
Image
RegionSingaporeSingapore
Endpoints
POST /v1/images/generations
POST /v1/images/generations
Capabilities
image generation image editing multi image multi reference transparent background text rendering
image generation image editing multi image text rendering multilingual text dense layouts photorealism

Qwen Image 2.1 vs Qwen Image 3.0: API pricing

Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.

Qwen Image 2.1 vs Qwen Image 3.0: API parameters

Request parameters each model lists on EmpirioLabs, with the allowed values or range where one applies. A dash marks a parameter the model does not list.

ParameterQwen Image 2.1Qwen Image 3.0
promptstringstring
model_variantqwen-image-2.1-pro, qwen-image-2.1-turbo Default: qwen-image-2.1-proqwen-image-3.0-pro, qwen-image-3.0 Default: qwen-image-3.0-pro
imagearrayarray
imagesarrayarray
aspect_ratioauto, 1:1, 16:9, 9:16, 3:2, 2:3, 4:3, 3:4, 5:4, 4:5 Default: autoauto, 1:1, 16:9, 9:16, 3:2, 2:3, 4:3, 3:4, 5:4, 4:5 Default: auto
resolutionauto, 1K, 2K Default: 2Kauto, 1K, 2K Default: 2K
sizestringstring
use_custom_sizeboolean Default: falseboolean Default: false
custom_width182 to 7240256 to 2048
custom_height182 to 7240256 to 2048
num_images1 to 6 Default: 11 to 6 Default: 1
negative_promptstringstring
prompt_extendboolean Default: trueboolean Default: true
prompt_extend_modedirect, agent Default: directdirect, agent Default: direct
seed0 to 21474836470 to 2147483647
watermarkboolean Default: falseboolean Default: false

Qwen Image 2.1 vs Qwen Image 3.0: limits and notes

Qwen Image 2.1

Qwen Image 2.1 combines Pro and Turbo image generation and editing in one model. Pro is selected by default, output starts at 2K, and aspect ratio starts in Auto. Turbo provides a faster, lower-cost option.

Variants

  • Choose qwen-image-2.1-pro for the highest image quality and complex edits.
  • Choose qwen-image-2.1-turbo for faster, lower-cost generation and routine edits.
  • Choose with model_variant. Without it, the model id qwen-image-2.1-turbo runs Turbo and every other id of this model runs Pro.

Modes

  • Text to image from a prompt.
  • Image editing and reference-guided generation from one to ten images.
  • Direct prompt extension works for generation and editing. Agent prompt extension provides deeper refinement for text-to-image requests only.

Transparent images

  • Output images are PNG files. For a transparent background, set prompt_extend to false and describe the image in this form: "This is an RGBA image with transparency. A glass perfume bottle. The image has alpha channel and the background is transparent."

Output limits

  • One to six output images per request.
  • 1K, 2K, automatic, aspect-ratio presets, or an exact custom size.
  • Exact and custom sizes stay between 512x512 and 2560x2560 pixels in total area, with an aspect ratio from 1:8 to 8:1.

Billing

  • Each output image is billed at its variant's rate. Reference images are not billed.

Content safety

Generated images pass an automated content-safety check. An image flagged as explicit is not returned. Because the image is generated before the check runs, a flagged generation is still billed.

Qwen Image 3.0

Qwen Image 3.0 combines Base and Pro image generation and editing in one model. Pro is selected by default, output starts at 2K, and aspect ratio starts in Auto. Base provides a lower-cost option for fast iteration.

Variants

  • Choose qwen-image-3.0-pro for photorealism, dense layouts, fine multilingual typography, and complex multi-image edits.
  • Choose qwen-image-3.0 for lower-cost generation and routine edits.
  • Choose with model_variant. Without it, the model ids qwen-image-3.0, alibaba/qwen-image-3.0 and alibaba/qwen-image-3-0 run Base and every other id of this model runs Pro.

Modes

  • Text to image from a prompt.
  • Image editing and reference-guided generation from one to three images.
  • Direct prompt extension works for generation and editing. Agent prompt extension provides deeper refinement for text-to-image requests only.

Output and input limits

  • One to six output images per request.
  • 1K, 2K, automatic, aspect-ratio presets, or an exact custom size.
  • Preset and custom sizes stay between 512x512 and 2048x2048 pixels, with each selected side up to 2048 pixels and aspect ratio from 1:8 to 8:1. Automatic sizing can choose its own dimensions within the 1K or 2K output tiers.
  • Input images can be JPG, JPEG, PNG, BMP, TIFF, WEBP, or GIF, up to 10 MB each.
  • Prompts support up to 4,500 tokens.

Billing

  • Base uses one output rate across 1K and 2K.
  • Pro outputs up to 2.25 megapixels use the 1K rate. Larger Pro outputs use the 2K rate.
  • Every reference image adds the input-image rate shown above.

Performance

  • 1K generations are optimized for interactive iteration. Complex 2K edits can take several minutes.

Content safety

Generated images pass an automated content-safety check. An image flagged as explicit is not returned. Because the image is generated before the check runs, a flagged generation is still billed.

How to call Qwen Image 2.1 and Qwen Image 3.0

Qwen Image 2.1 runs through POST /v1/images/generations. The request returns a job_id right away; poll GET /v1/jobs/{job_id} until the job completes and read the output URLs from the result. Or add "sync": true to skip polling: the request stays open and returns the finished OpenAI-style image response directly, so OpenAI SDKs work as-is. Both models are called through the same endpoint. Set model to qwen-image-2-1 or qwen-image-3-0. Get an API key from the EmpirioLabs dashboard.

cURL: submit the job
curl https://api.empiriolabs.ai/v1/images/generations \
  -H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-image-2-1",
    "prompt": "Describe what you want Qwen Image 2.1 to generate."
  }'

Qwen Image 2.1 vs Qwen Image 3.0: tests and guides

Prompt tests and comparison runs that cover both models.

Qwen Image 2.1 vs Qwen Image 3.0: common questions

What is the difference between Qwen Image 2.1 and Qwen Image 3.0?

Qwen Image 2.1 is the newer release (Oct 2, 2026); Qwen Image 3.0 was released on Jul 21, 2026. Capabilities listed only for Qwen Image 2.1: multi reference, transparent background. Capabilities listed only for Qwen Image 3.0: multilingual text, dense layouts, photorealism. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.

Which is newer, Qwen Image 2.1 or Qwen Image 3.0?

Qwen Image 2.1 is the newer release (Oct 2, 2026); Qwen Image 3.0 was released on Jul 21, 2026.

Which has the lower rate, Qwen Image 2.1 or Qwen Image 3.0?

The two models are priced on different units or tiers, so compare the live rate cards on this page. They always match what the API charges.

Can I switch between Qwen Image 2.1 and Qwen Image 3.0 without rebuilding my integration?

Yes. Both models use POST /v1/images/generations with the same EmpirioLabs API key, so most integrations switch by changing the model value. Check the parameters table on this page first if you rely on a model-specific parameter.

Can I try Qwen Image 2.1 and Qwen Image 3.0 in the browser before integrating?

Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.

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